Algae Illumination Profile via CFD Trajectory Simulation
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Solution Overview
Problem
Current methods for developing commercial-scale algae biofuels face challenges in identifying algae strains that can effectively grow in various commercial environments, as laboratory settings often lack exposure to external variables like sunlight and temperature, making it difficult to replicate real-world conditions for testing.
Innovation Solution
The method involves calculating particle trajectories within a reference volume using computational fluid dynamics to determine an illumination profile that simulates the light exposure algae would experience in outdoor ponds or photobioreactors, allowing for controlled growth and characterization of algae samples in a controlled environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If algae are grown in conventional laboratory settings with controlled conditions, then repeatability and consistency of growth data are improved, but the ability to predict commercial environment performance deteriorates
Solution Approach 1:
The patent creates a virtual photobioreactor model that copies the essential characteristics of commercial algae growth environments (light intensity, temperature, mixing patterns) into a controlled laboratory setting. This allows researchers to replicate commercial conditions in a reproducible manner, enabling both reliability and adaptability simultaneously.
Solution Approach 2:
The system dynamically adjusts environmental parameters (light intensity, temperature, mixing rate) to match specific commercial environment conditions. By changing these parameters to represent different commercial settings, the same laboratory apparatus can predict performance across various commercial environments while maintaining controlled, repeatable measurements.
2Adaptability or versatility
If algae are grown in outdoor ponds or large photobioreactors to simulate commercial conditions, then predictability of commercial environment performance is improved, but control over growth variables and measurement precision deteriorates
Solution Approach 1:
The patent segments the large-scale photobioreactor into multiple smaller, independently controllable sections. Each section can be optimized for precise measurement while collectively representing the overall commercial environment conditions. This segmentation allows for both representative modeling and precise measurement of individual growth parameters.
Solution Approach 2:
The system introduces sensors and monitoring devices as intermediaries between the algae culture and the measurement system. These intermediaries continuously monitor growth parameters (cell density, chlorophyll content, biomass) and provide precise data while allowing the system to maintain representative commercial conditions.
3Measurement precision
If computational fluid dynamics modeling is used to simulate particle trajectories, then accuracy of light exposure prediction is improved, but device complexity and computational resources required increase
Solution Approach 1:
The patent performs preliminary computational fluid dynamics simulations to establish particle trajectories and light exposure patterns before actual algae growth experiments. These pre-calculated models provide accurate light exposure predictions that guide the physical experiment design, reducing the need for complex real-time measurements and lowering overall system complexity.
Solution Approach 2:
The system replaces complex mechanical measurement systems with computational modeling. Instead of using elaborate sensors and instruments to directly measure light exposure in every possible position, the patent uses CFD simulations to calculate and predict light distribution patterns, significantly simplifying the physical measurement infrastructure while maintaining high accuracy.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables the prediction and characterization of algal behavior and properties under simulated outdoor conditions, facilitating the comparison of different algae strains and environmental impacts on growth and productivity, thereby aiding in the development of commercial-scale algae biofuel production.
Implementation Method 1
The methods include using computational fluid dynamics to calculate trajectories of algae particles in a photobioreactor
Implementation Method 2
The plurality of light sources are positioned to illuminate the cross-sectional area of the growth vessel, which allows light to be incident on the algae sample
Implementation Method 3
an illumination profile can be determined by obtaining an illumination intensity corresponding to the plurality of position values and associated times
Data Source
AI summary
Systems and methods are provided for using a growth vessel to simulate algae growth and/or productivity in a reference environment, such as an open pond, a closed photobioreactor, or a hybrid system. Based on predicted algae sample trajectories in the reference environment, an illumination profile is developed. An algae sample in the growth vessel can then be exposed to the illumination profile under controlled conditions. Properties of algae in the reference environment can then be characterized based on the sample exposed to the illumination profile.